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by io.github.pipeworx-io

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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds substantial behavioral context beyond the annotations: it explains OAuth requirements, SMS phone verification and the 10/day cap, webhook signing secret issuance, and auto-disabling after 10 consecutive failures. These details are not present in the annotations and significantly improve understanding of side effects and constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded and every sentence carries information, but it is a dense block of text covering multiple types and deliveries. Given the tool's complexity, it remains efficient, though the length prevents a perfect score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with nested objects and no output schema, the description is remarkably complete: it covers all supported types, parameter shapes, delivery channels, authentication requirements, return value, and operational details like SMS caps and webhook signing. No significant gaps were found.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description enriches parameters with concrete examples, such as items:["5.02"] = officer change and params:{topic:"fed"}. It also adds critical caveats for delivery parameters (phone must be verified, webhook secret returned only once) that are absent from the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: 'Create a proactive monitoring subscription to a live-data event stream.' It also specifies the primary return value ('Returns the new subscription id') and enumerates supported types, making it distinct from siblings like list_subscriptions, unsubscribe, and recent_alerts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool, including a prerequisite ('Requires a Pipeworx OAuth account') and an exclusion ('anonymous + BYO cannot persist subscriptions'). It also details delivery options and highlights the always-on feed, suggesting how to consume alerts. However, it does not explicitly compare against alternative tools like recent_alerts for one-off reads, so it falls short of 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0
Disambiguation2/5

Many tools have detailed, differentiated roles, but there are several overlapping clusters: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language data questions, and ask_pipeworx_beta is currently identical to ask_pipeworx. Onboarding/discovery and Polymarket edge tools also blur together, so an agent can easily select the wrong entry point.

Naming Consistency3/5

Names are uniformly snake_case and readable, with coherent subfamilies like ask_pipeworx*, polymarket_*, and list_*. But conventions are mixed across the set: bare verbs (remember, forget, subscribe), noun phrases (entity_profile, recent_changes), and adjective-led names (recent_alerts) exist alongside verb_noun names, so there is no consistent pattern.

Tool Count2/5

35 tools is already in the 'too many' range, and only four (get_exercise, list_exercises, list_equipment, list_muscles) belong to a wger fitness server. The remaining ~31 tools are unrelated Pipeworx/prediction-market/memory utilities, making the count inappropriate for the apparent domain.

Completeness1/5

As a wger fitness server, the surface is a read-only reference slice: exercise, equipment, and muscle lookups, with no workout routine management, user data, or create/update/delete operations for any wger resource. Even ignoring the unrelated Pipeworx tools, the fitness domain has severe gaps that would block most real usage.

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